Market-based multi-robot coalition formation

Task allocation is an issue that every multi-robot system must address. Recent task allocation solutions propose, an auction based approach wherein robots bid for tasks based on cost functions for performing a task. This paper presents RACHNA, a novel architecture for multi-robot task allocation based on a modified algorithm for the winner determination problem in multi-unit combinatorial auctions. A more generic utility based framework is proposed to accommodate different types of tasks and task environments. Preliminary experiments yield promising results demonstrating the system's superiority over simple task allocation techniques.